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Machine Learning and AI Scientist at GE Vernova Advanced Research Center
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Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Building solutions for industrial AI, with applications ranging from wind power to nuclear energy, to realize a more verdant future.
Syracuse University
Master of Science (MS), Electrical Engineering
January 1, 2016 – January 1, 2020
Syracuse University
Doctor of Philosophy (Ph.D.), Electrical and Computer Engineering
January 1, 2004 – January 1, 2014
University
Bachelor of Engineering (B.E.), Electronics and Communications Engineering
January 1, 1999 – January 1, 2003
GE Vernova
Lead Scientist
April 1, 2024 – Present
Los Angeles Metropolitan Area · Remote
GE Global Research
Machine Learning Researcher
December 1, 2015 – March 1, 2024
Andro Computational Solutions, LLC
Associate Research Senior Scientist
July 1, 2015 – November 1, 2015
Rome, NY
Syracuse University
Postdoctoral Intern
March 1, 2015 – July 1, 2015
Syracuse, NY
Syracuse University
Graduate Research Assistant
August 1, 2006 – December 1, 2014
Greater Syracuse-Auburn Area
Syracuse University
Graduate Researcher
May 1, 2005 – July 1, 2006
Greater Syracuse-Auburn Area
Indian Institute of Technology, Delhi
Research Associate
December 1, 2003 – August 1, 2004
Greater Delhi Area
Indian Institute of Technology, Delhi
Undergraduate Intern
January 1, 2003 – March 1, 2003
Greater Delhi Area
Detecting & classifying phenological events in the presence of anthropogenic clutter
November 1, 2013 – Present
Analyzing acoustic data collected at various National Ecological Observatory Network (NEON) locations. Discovering diel and long-term patterns to help understand the consequences of human activity on phenology.
Ultra hi-resolution 3D soft tissue image reconstruction
January 1, 2012 – Present
Fusion of images acquired from micro-CT and confocal laser scanning microscope (CLSM) to generate ultra hi-resolution 3D images.
Neuronal nuclei density estimation
August 1, 2006 – Present
Processed microscope (LSM) images to estimate density of neuronal nuclei. Applications extend to areas where automatic methods to estimate cellular density in biological tissue is desirable.
Cultural Fit Analysis
The candidate's project history is heavily skewed towards academic research and industrial R&D, with a focus on complex scientific and engineering problems. While this demonstrates intellectual curiosity and a drive for innovation, the projects lack explicit mention of business impact, stakeholder communication, or agile methodologies commonly found in corporate data analyst roles. The transition from a research scientist to a data analyst role would require an adaptation to business-driven problem-solving and potentially a more collaborative, iterative development environment. The projects are diverse in their scientific domain but less so in their application to typical business data analysis challenges.
Soft Skills & Operational Fit
The candidate's extensive research background suggests strong problem-solving, analytical thinking, and independent work capabilities. The descriptions of collaborative projects (e.g., with biophysicists, mathematicians, and computer scientists) indicate an ability to work in interdisciplinary teams. However, the resume does not explicitly detail communication or leadership roles beyond 'Lead Scientist', making it difficult to fully assess operational fit in a team-lead or client-facing data analyst role.